Physiological variation in metabolic phenotyping and functional genomic studies: use of orthogonal signal correction and PLS-DA

Balancing the Equation: A Natural History of Trimethylamine and Trimethylamine-N-oxide

Trimethylamine (TMA) and its N-oxide (TMAO) are ubiquitous in prokaryote and eukaryote organisms as well as in the environment, reflecting their fundamental importance in evolutionary biology, and their diverse biochemical functions. Both metabolites have multiple biological roles including cell-signaling. Much attention has focused on the significance of serum and urinary TMAO in cardiovascular disease risk, yet this is only one of the many facets of a deeper TMA-TMAO partnership that reflects the significance of these metabolites in multiple biological processes spanning animals, plants, bacteria, and fungi. We report on analytical methods for measuring TMA and TMAO and attempt to critically synthesize and map the global functions of TMA and TMAO in a systems biology framework.

Malignancy prediction among tissues from Oral SCC patients including neck invasions: a 1H HRMAS NMR based metabolomic study

INTRODUCTION

Oral cancer is a sixth commonly occurring cancer globally. The use of tobacco and alcohol consumption are being considered as the major risk factors for oral cancer. The metabolic profiling of tissue specimens for developing carcinogenic perturbations will allow better prognosis.

OBJECTIVES

To profile and generate precise ¹H HRMAS NMR spectral and quantitative statistical models of oral squamous cell carcinoma (OSCC) in tissue specimens including tumor, bed, margin and facial muscles. To apply the model in blinded prediction of malignancy among oral and neck tissues in an unknown set of patients suffering from OSCC along with neck invasion.

METHODS

Statistical models of ¹H HRMAS NMR spectral data on 180 tissues comprising tumor, margin and bed from 43 OSCC patients were performed. The combined metabolites, lipids spectral intensity and concentration-based malignancy prediction models were proposed. Further, 64 tissue specimens from twelve patients, including neck invasions, were tested for malignancy in a blinded manner.

RESULTS

Forty-eight metabolites including lipids have been quantified in tumor and adjacent tissues. All metabolites other than lipids were found to be upregulated in malignant tissues except for ambiguous glucose. All of three prediction models have successfully identified malignancy status among blinded set of 64 tissues from 12 OSCC patients with an accuracy of above 90%.

CONCLUSION

The efficiency of the models in malignancy prediction based on tumor induced metabolic perturbations supported by histopathological validation may revolutionize the OSCC assessment. Further, the results may enable machine learning to trace tumor induced altered metabolic pathways for better pattern recognition. Thus, it complements the newly developed REIMS-MS iKnife real time precession during surgery.

1H NMR metabolomics applied to Bordeaux red wines

The q-NMR metabolomics has already demonstrated its potential for classifying wines of different geographical origins, grape varieties, or vintages. This study focuses on the characterisation of Bordeaux red wines, seeking to discriminate them from others produced in the major French wine regions. A sampling of 224 commercial French wines was analysed by ¹H NMR and forty compounds were quantified. Non-supervised and supervised statistical analyses revealed a singular imprint of Bordeaux wines in comparison with other French wines, with classification rates ranging from 71% to 100%. Within the Bordeaux vineyards, red wines from the different Bordeaux subdivisions were analysed from different vintages. Our results indicate that q-NMR metabolomics enables the differentiation of Médoc and Libournais vineyard highlighting the most discriminant constituents. In addition, the effects of wine evolution during bottle aging and vintage on Bordeaux red wines were pointed out and discussed.

The impact of acute thermal stress on the metabolome of the black rockfish (Sebastes schlegelii)

Acute change in water temperature causes heavy economic losses in the aquaculture industry. The present study investigated the metabolic and molecular effects of acute thermal stress on black rockfish (Sebastes schlegelii). Gas chromatography time-of-flight mass spectrometry (GC-TOF-MS)-based metabolomics was used to investigate the global metabolic response of black rockfish at a high water temperature (27°C), low water temperature (5°C) and normal water temperature (16°C). Metabolites involved in energy metabolism and basic amino acids were significantly increased upon acute exposure to 27°C (P < 0.05), and no change in metabolite levels occurred in the low water temperature group. However, certain fatty acid levels were elevated after cold stress (P < 0.05), and this effect was not observed in the 27°C group, suggesting that acute high and low temperature exposures caused different physiological responses. Using quantitative real-time PCR, we analyzed the expression of ubiquitin (ub), hypoxia-inducible factor (hif), lactate dehydrogenase (ldh), and acetyl-CoA carboxylase (acac). Higher expression levels of ub, hif, and ldh (P < 0.05) were observed in the high water temperature group, but no changes in these expression levels occurred in the low water temperature group. Our findings provide a potential metabolic profile for black rockfish when exposed to acute temperature stress and provide some insights into host metabolic and molecular responses to thermal stress.

Metabolic responses to elevated pCO2 in the gills of the Pacific oyster (Crassostrea gigas) using a GC-TOF-MS-based metabolomics approach

Rising atmospheric carbon dioxide (CO₂), primarily from anthropogenic emissions, are resulting in increasing absorption of CO₂ by the oceans, leading to a decline in oceanic pH in a process known as ocean acidification (OA). There is a growing body of evidence demonstrating the potential effect of OA on the energetics/physiology and consequently life-history traits of commensally important marine organisms. However, despite this little is known of how fundamental metabolic pathways that underpin changes in organismal physiology are affected by OA. Consequently, a gas chromatography time-of-flight mass spectrometry (GC-TOF-MS) based metabolic profiling approach was applied to examine the metabolic responses of Crassostrea gigas to elevated pCO₂ levels, under otherwise natural field conditions. Oysters were exposed natural environmental pCO₂ (~625.40 μatm) and elevated pCO₂ (~1432.94 μatm) levels for 30 days. Results indicated that 36 differential metabolites were identified. Differential metabolites were mapped in the Kyoto Encyclopedia of Genes and Genomes (KEGG) database to search for the related metabolic pathways. Pathway enrichment analysis indicates that alanine, aspartate and glutamate metabolism and glycine, serine and threonine metabolism were the most statistically enriched pathways. Further analysis suggested that elevated pCO₂ disturb the TCA cycle via succinate accumulation and C. gigas most likely adjust their energy metabolic via alanine and GABA accumulation accordingly to cope with elevated pCO₂. These findings provide an understanding of the molecular mechanisms involved in modulating C. gigas metabolism under elevated pCO₂.

Antibiotic treatment triggers gut dysbiosis and modulates metabolism in a chicken model of gastro-intestinal infection

Background

Infection of the digestive track by gastro-intestinal pathogens results in the development of symptoms ranging from mild diarrhea to more severe clinical signs such as dysentery, severe dehydration and potentially death. Although, antibiotics are efficient to tackle infections, they also trigger dysbiosis that has been suggested to result in variation in weight gain in animal production systems.

Results

Here is the first study demonstrating the metabolic impact of infection by a gastro-intestinal pathogen (Brachyspira pilosicoli) and its resolution by antibiotic treatment (tiamulin) on the host (chicken) systemic metabolism and gut microbiota composition using high-resolution ¹H nuclear magnetic resonance (NMR) spectroscopy and 16S rDNA next generation sequencing (NGS). Clear systemic metabolic markers of infections such as glycerol and betaine were identified. Weight loss in untreated animals was in part explained by the observation of a modification of systemic host energy metabolism characterized by the utilization of glycerol as a glucose precursor. However, antibiotic treatment triggered an increased VLDL/HDL ratio in plasma that may contribute to reducing weight loss observed in treated birds. All metabolic responses co-occurred with significant shift of the microbiota upon infection or antibiotic treatment.

Conclusion

This study indicates that infection and antibiotic treatment trigger dysbiosis that may impact host systemic energy metabolism and cause phenotypic and health modifications.

Electronic supplementary material

The online version of this article (10.1186/s12917-018-1761-0) contains supplementary material, which is available to authorized users.

Alteration in lipid composition differentiates breast cancer tissues: a 1H HRMAS NMR metabolomic study

INTRODUCTION

Breast cancer is the most frequent diagnosed cancer among women with a mortality rate of 15% of all cancer related deaths in women. Breast cancer is heterogeneous in nature and produces plethora of metabolites allowing its early detection using molecular diagnostic techniques like magnetic resonance spectroscopy.

OBJECTIVES

To evaluate the variation in metabolic profile of breast cancer focusing on lipids as triglycerides (TG) and free fatty acids (FFA) that may alter in malignant breast tissues and lymph nodes from adjacent benign breast tissues by HRMAS ¹H NMR spectroscopy.

METHODS

The ¹H NMR spectra recorded on 173 tissue specimens comprising of breast tumor tissues, adjacent tissues, few lymph nodes and overlying skin tissues obtained from 67 patients suffering from breast cancer. Multivariate statistical analysis was employed to identify metabolites acting as major confounders for differentiation of malignancy.

RESULT

Reduction in lipid content were observed in malignant breast tissues along with a higher fraction of FFA. Four small molecule metabolites e.g., choline containing compounds (Chocc), taurine, glycine, and glutamate were also identified as major confounders. The test set for prediction provided sensitivity and specificity of more than 90% excluding the lymph nodes and skin tissues.

CONCLUSION

Fatty acids composition in breast cancer using in vivo magnetic resonance spectroscopy (MRS) is gaining its importance in clinical settings (Coum et al. in Magn Reson Mater Phys Biol Med 29:1-4, 2016). The present study may help in future for precise evaluation of lipid classification including small molecules as a source of early diagnosis of invasive ductal carcinoma by employing in vivo magnetic resonance spectroscopic methods.

Metabotyping and its application in targeted nutrition: an overview

Metabolic diversity leads to differences in nutrient requirements and responses to diet and medication between individuals. Using the concept of metabotyping – that is, grouping metabolically similar individuals – tailored and more efficient recommendations may be achieved. The aim of this study was to review the current literature on metabotyping and to explore its potential for better targeted dietary intervention in subjects with and without metabolic diseases. A comprehensive literature search was performed in PubMed, Google and Google Scholar to find relevant articles on metabotyping in humans including healthy individuals, population-based samples and patients with chronic metabolic diseases. A total of thirty-four research articles on human studies were identified, which established more homogeneous subgroups of individuals using statistical methods for analysing metabolic data. Differences between studies were found with respect to the samples/populations studied, the clustering variables used, the statistical methods applied and the metabotypes defined. According to the number and type of the selected clustering variables, the definitions of metabotypes differed substantially; they ranged between general fasting metabotypes, more specific fasting parameter subgroups like plasma lipoprotein or fatty acid clusters and response groups to defined meal challenges or dietary interventions. This demonstrates that the term ‘metabotype’ has a subjective usage, calling for a formalised definition. In conclusion, this literature review shows that metabotyping can help identify subgroups of individuals responding differently to defined nutritional interventions. Targeted recommendations may be given at such metabotype group levels. Future studies should develop and validate definitions of generally valid metabotypes by exploiting the increasingly available metabolomics data sets.

Ion mobility spectrometry combined with ultra performance liquid chromatography/mass spectrometry for metabolic phenotyping of urine: Effects of column length, gradient duration and ion mobility spectrometry on metabolite detection

The need for rapid and efficient high throughput metabolic phenotyping (metabotyping) in metabolomic/metabonomic studies often requires compromises to be made between analytical speed and metabolome coverage. Here the effect of column length (150, 75 and 30 mm) and gradient duration (15, 7.5 and 3 min respectively) on the number of features detected when untargeted metabolic profiling of human urine using reversed-phase gradient ultra performance chromatography with, and without, ion mobility spectrometry, has been examined. As would be expected, reducing column length from 150 to 30 mm, and gradient duration, from 15 to 3 min, resulted in a reduction in peak capacity from 311 to 63 and a similar reduction in the number of features detected from over ca. 16,000 to ca. 6500. Under the same chromatographic conditions employing UPLC/IMS/MS to provide an additional orthogonal separation resulted in an increase in the number of MS features detected to nearly 20,000 and ca. 7500 for the 150 mm and the 30 mm columns respectively. Based on this limited study the potential of LC/IMS/MS as a tool for improving throughput and increasing metabolome coverage clearly merits further in depth study.

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Ion mobility spectrometry (IMS) significantly increased the number of analytes detected during the LC-MS of urine.

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Nearly ca. 20,000 features were seen for urine using LC-IMS-MS in a 15 min analysis compared to ca. 16,000 by LC-MS alone.

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In a 3 min analysis using a 30 mm column nearly 7600 features were detected with combined IMS and MS.

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For high throughput analysis a 75 mm column and a 3 min analysis was a good compromise between speed and features detected.

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The use of IMS also improved the quality of the mass spectra obtained.

Application of 1H NMR spectroscopy to the metabolic phenotyping of rodent brain extracts: A metabonomic study of gut microbial influence on host brain metabolism

¹H NMR Spectroscopy has been applied to determine the neurochemical profiles of brain extracts from the frontal cortex and hippocampal regions of germ free and normal mice and rats. The results revealed a number of differences between germ free (GF) and conventional (CV) rats or specific pathogen-free (SPF) mice with microbiome-associated metabolic variation found to be both species- and region-dependent. In the mouse, the GF frontal cortex contained lower amounts of creatine, N-acetyl-aspartate (NAA), glycerophosphocholine and lactate, but greater amounts of choline compared to that of specific pathogen free (SPF) mice. In the hippocampus, the GF mice had greater creatine, NAA, lactate and taurine content compared to those of the SPF animals, but lower relative quantities of succinate and an unidentified lipid-related component. The GF rat frontal cortex contained higher relative quantities of lactate, creatine and NAA compared to the CV animals whilst the GF hippocampus was characterized by higher taurine and phosphocholine concentrations and lower quantities of NAA, N-acetylaspartylglutamate and choline compared to the CV animals. Of note is that, in both rat and mouse brain extracts, concentrations of hippocampal taurine were found to be greater in the absence of an established microbiome. The results provide further evidence that brain biochemistry can be influenced by gut microbial status, specifically metabolites involved in energy metabolism demonstrating biochemical dialogue between the microbiome and brain.

High-Speed Quantitative UPLC-MS Analysis of Multiple Amines in Human Plasma and Serum via Precolumn Derivatization with 6-Aminoquinolyl-N-hydroxysuccinimidyl Carbamate: Application to Acetaminophen-Induced Liver Failure

A targeted reversed-phase gradient UPLC-MS/MS assay has been developed for the quantification /monitoring of 66 amino acids and amino-containing compounds in human plasma and serum using precolumn derivatization with 6-aminoquinolyl-N-hydroxysuccinimidyl carbamate (AccQTag Ultra). Derivatization of the target amines required minimal sample preparation and resulted in analytes with excellent chromatographic and mass spectrometric detection properties. The resulting method, which requires only 10 μL of sample, provides the reproducible and robust separation of 66 analytes in 7.5 min, including baseline resolution of isomers such as leucine and isoleucine. The assay has been validated for the quantification of 33 amino compounds (predominantly amino acids) over a concentration range from 2 to 20 and 800 μM. Intra- and interday accuracy of between 0.05 and 15.6 and 0.78-13.7% and precision between 0.91 and 16.9% and 2.12-15.9% were obtained. A further 33 biogenic amines can be monitored in samples for relative changes in concentration rather than quantification. Application of the assay to samples derived from healthy controls and patients suffering from acetaminophen (APAP, paracetamol)-induced acute liver failure (ALF) showed significant differences in the amounts of aromatic and branched chain amino acids between the groups as well as a number of other analytes, including the novel observation of increased concentrations of sarcosine in ALF patients. The properties of the developed assay, including short analysis time, make it suitable for high-throughput targeted UPLC-ESI-MS/MS metabonomic analysis in clinical and epidemiological environments.

(1)H NMR and MS based metabolomics study of the therapeutic effect of Cortex Fraxini on hyperuricemic rats

ETHNOPHARMACOLOGICAL RELEVANCE

Cortex Fraxini (CF) is an important traditional Chinese herbal medicine used for the treatment of gout and hyperuricemia.

AIM OF THE STUDY

The aim of this study was to evaluate the anti-hyperuricemic effect of CF on hyperuricemic rats and to investigate its mechanism of action.

MATERIALS AND METHODS

Metabolomics based on NMR and MS was used to study the therapeutic effect of CF on hyperuricemic rats. Plasma determination of uric acid (UA) showed that CF treatment markedly improved the UA level. Subsequently, metabolomics analysis was conducted using samples of plasma, kidney and urine, and orthogonal partial least squares-discriminant analysis (OPLS-DA) combined with principal component analysis (PCA) were used to detect potential biomarkers.

RESULTS

A total of 26 biomarkers were identified as being primarily involved in amino acid metabolism, lipid metabolism, purine metabolism, amino acid metabolism and carbohydrate metabolism, and hyperuricemia can disturb the balance of many of these metabolic pathways in vivo.

CONCLUSIONS

The variations in biomarkers revealed the therapeutic mechanism of CF, and a number of these biomarkers are not only significant for early diagnosis but also for predicting hyperuricemia.

NMR-based fecal metabolomics fingerprinting as predictors of earlier diagnosis in patients with colorectal cancer

Colorectal cancer (CRC) is a growing cause of mortality in developing countries, warranting investigation into its earlier detection for optimal disease management. A metabolomics based approach provides potential for noninvasive identification of biomarkers of colorectal carcinogenesis, as well as dissection of molecular pathways of pathophysiological conditions. Here, proton nuclear magnetic resonance spectroscopy (1HNMR) -based metabolomic approach was used to profile fecal metabolites of 68 CRC patients (stage I/II=20; stage III=25 and stage IV=23) and 32 healthy controls (HC). Pattern recognition through principal component analysis (PCA) and orthogonal partial least squares-discriminant analysis (OPLS-DA) was applied on 1H-NMR processed data for dimension reduction. OPLS-DA revealed that each stage of CRC could be clearly distinguished from HC based on their metabolomic profiles. Successive analyses identified distinct disturbances to fecal metabolites of CRC patients at various stages, compared with those in cancer free controls, including reduced levels of acetate, butyrate, propionate, glucose, glutamine, and elevated quantities of succinate, proline, alanine, dimethylglycine, valine, glutamate, leucine, isoleucine and lactate. These altered fecal metabolites potentially involved in the disruption of normal bacterial ecology, malabsorption of nutrients, increased glycolysis and glutaminolysis. Our findings revealed that the fecal metabolic profiles of healthy controls can be distinguished from CRC patients, even in the early stage (stage I/II), highlighting the potential utility of NMR-based fecal metabolomics fingerprinting as predictors of earlier diagnosis in CRC patients.

Assessing Cardiac Metabolism: A Scientific Statement From the American Heart Association

In a complex system of interrelated reactions, the heart converts chemical energy to mechanical energy. Energy transfer is achieved through coordinated activation of enzymes, ion channels, and contractile elements, as well as structural and membrane proteins. The heart's needs for energy are difficult to overestimate. At a time when the cardiovascular research community is discovering a plethora of new molecular methods to assess cardiac metabolism, the methods remain scattered in the literature. The present statement on "Assessing Cardiac Metabolism" seeks to provide a collective and curated resource on methods and models used to investigate established and emerging aspects of cardiac metabolism. Some of those methods are refinements of classic biochemical tools, whereas most others are recent additions from the powerful tools of molecular biology. The aim of this statement is to be useful to many and to do justice to a dynamic field of great complexity.

Mechanism of Xinfeng Capsule on Adjuvant-Induced Arthritis via Analysis of Urinary Metabolomic Profiles

We aimed to explore the potential effects of Xinfeng capsule (XFC) on urine metabolic profiling in adjuvant-induced arthritis (AA) rats by using gas chromatography time-of-flight mass spectrometry (GC-TOF/MS). GC-TOF/MS technology was combined with multivariate statistical approaches, such as principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA), and orthogonal projections to latent structures discriminant analysis (OPLS-DA). These methods were used to distinguish the healthy group, untreated group, and XFC treated group and elucidate potential biomarkers. Nine potential biomarkers such as hippuric acid, adenine, and L-dopa were identified as potential biomarkers, indicating that purine metabolism, fat metabolism, amino acid metabolism, and energy metabolism were disturbed in AA rats. This study demonstrated that XFC is efficacious for RA and explained its potential metabolomics mechanism.

Revealing Potential Biomarkers of Functional Dyspepsia by Combining 1H NMR Metabonomics Techniques and an Integrative Multi-objective Optimization Method

Metabonomics methods have gradually become important auxiliary tools for screening disease biomarkers. However, recognition of metabolites or potential biomarkers closely related to either particular clinical symptoms or prognosis has been difficult. The current study aims to identify potential biomarkers of functional dyspepsia (FD) by a new strategy that combined hydrogen nuclear magnetic resonance (¹H NMR)-based metabonomics techniques and an integrative multi-objective optimization (LPIMO) method. First, clinical symptoms of FD were evaluated using the Nepean Dyspepsia Index (NDI), and plasma metabolic profiles were measured by ¹H NMR. Correlations between the key metabolites and the NDI scores were calculated. Then, LPIMO was developed to identify a multi-biomarker panel by maximizing diagnostic ability and correlation with the NDI score. Finally, a KEGG database search elicited the metabolic pathways in which the potential biomarkers are involved. The results showed that glutamine, alanine, proline, HDL, β-glucose, α-glucose and LDL/VLDL levels were significantly altered in FD patients. Among them, phosphatidycholine (PtdCho) and leucine/isoleucine (Leu/Ile) were positively and negatively correlated with the NDI Symptom Index (NDSI) respectively. Our procedure not only significantly improved the credibility of the biomarkers, but also demonstrated the potential of further explorations and applications to diagnosis and treatment of complex disease.

Zebrafish as a Model for Systems Medicine R&D: Rethinking the Metabolic Effects of Carrier Solvents and Culture Buffers Determined by (1)H NMR Metabolomics

Zebrafish is a frequently employed model organism in systems medicine and biomarker discovery. A crosscutting fundamental question, and one that has been overlooked in the field, is the "system-wide" (omics) effects induced in zebrafish by metabolic solvents and culture buffers. Indeed, any bioactivity or toxicity test requires that the target compounds are dissolved in an appropriate nonpolar solvent or aqueous media. It is important to know whether the solvent or the buffer itself has an effect on the zebrafish model organism. We evaluated the effects of two organic carrier solvents used in research with zebrafish, as well as in drug screening: dimethyl sulfoxide (DMSO) and ethanol, and two commonly used aqueous buffers (egg water and Hank's balanced salt solution). The effects of three concentrations (0.01, 0.1, and 1%) of DMSO and ethanol were tested in the 5-day-old zebrafish embryo using proton nuclear magnetic resonance ((1)H NMR) based metabolomics. DMSO (1% and 0.1%, but not 0.01%) exposure significantly decreased the levels of adenosine triphosphate (ATP), betaine, alanine, histidine, lactate, acetate, and creatine (p < 0.05). By contrast, ethanol exposure did not alter the embryos' metabolome at any concentration tested. The two different aqueous media noted above impacted the zebrafish embryo metabolome as evidenced by changes in valine, alanine, lactate, acetate, betaine, glycine, glutamate, adenosine triphosphate, and histidine. These results show that DMSO has greater effects on the embryo metabolome than ethanol, and thus is used with caution as a carrier solvent in zebrafish biomarker research and oral medicine. Moreover, the DMSO concentration should not be higher than 0.01%. Careful attention is also warranted for the use of the buffers egg water and Hank's balanced salt solution in zebrafish. In conclusion, as zebrafish is widely used as a model organism in life sciences, metabolome changes induced by solvents and culture buffers warrant further attention for robust systems science, and precision biomarkers that will stand the test of time.

Nuclear Magnetic Resonance (NMR) Spectroscopy For Metabolic Profiling of Medicinal Plants and Their Products

NMR spectroscopy has multidisciplinary applications, including excellent impact in metabolomics. The analytical capacity of NMR spectroscopy provides information for easy qualitative and quantitative assessment of both endogenous and exogenous metabolites present in biological samples. The complexity of a particular metabolite and its contribution in a biological system are critically important for understanding the functional state that governs the organism's phenotypes. This review covers historical aspects of developments in the NMR field, its applications in chemical profiling, metabolomics, and quality control of plants and their derived medicines, foods, and other products. The bottlenecks of NMR in metabolic profiling are also discussed, keeping in view the future scope and further technological interventions.

Strategy for NMR metabolomic analysis of urine in mouse models of obesity--from sample collection to interpretation of acquired data

The mouse model of monosodium glutamate induced obesity was used to examine and consequently optimize the strategy for analysis of urine samples by NMR spectroscopy. A set of nineteen easily detectable metabolites typical in obesity-related studies was selected. The impact of urine collection protocol, choice of (1)H NMR pulse sequence, and finally the impact of the normalization method on the detected concentration of selected metabolites were investigated. We demonstrated the crucial effect of food intake and diurnal rhythms resulting in the choice of a 24-hour fasting collection protocol as the most convenient for tracking obesity-induced increased sensitivity to fasting. It was shown that the Carr-Purcell-Meiboom-Gill (CPMG) experiment is a better alternative to one-dimensional nuclear Overhauser enhancement spectroscopy (1D-NOESY) for NMR analysis of mouse urine due to its ability to filter undesirable signals of proteins naturally present in rodent urine. Normalization to total spectral area provided comparable outcomes as did normalization to creatinine or probabilistic quotient normalization in the CPMG-based model. The optimized approach was found to be beneficial mainly for low abundant metabolites rarely monitored due to their overlap by strong protein signals.

1H nuclear magnetic resonance-based extracellular metabolomic analysis of multidrug resistant Tca8113 oral squamous carcinoma cells

A major obstacle of successful chemotherapy is the development of multidrug resistance (MDR) in the cancer cells, which is difficult to reverse. Metabolomic analysis, an emerging approach that has been increasingly applied in various fields, is able to reflect the unique chemical fingerprints of specific cellular processes in an organism. The assessment of such metabolite changes can be used to identify novel therapeutic biomarkers. In the present study, ¹H nuclear magnetic resonance (NMR) spectroscopy was used to analyze the extracellular metabolomic spectrum of the Tca8113 oral squamous carcinoma cell line, in which MDR was induced using the carboplatin (CBP) and pingyangmycin (PYM) chemotherapy drugs in vitro. The data were analyzed using the principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) methods. The results demonstrated that the extracellular metabolomic spectrum of metabolites such as glutamate, glycerophosphoethanol amine, α-Glucose and β-Glucose for the drug-induced Tca8113 cells was significantly different from the parental Tca8113 cell line. A number of biochemicals were also significantly different between the groups based on their NMR spectra, with drug-resistant cells presenting relatively higher levels of acetate and lower levels of lactate. In addition, a significantly higher peak was observed at δ 3.35 ppm in the spectrum of the PYM-induced Tca8113 cells. Therefore, ¹H NMR-based metabolomic analysis has a high potential for monitoring the formation of MDR during clinical tumor chemotherapy in the future.

1H NMR-based metabolomics investigation of copper-laden rat: a model of Wilson's disease

BACKGROUND AND PURPOSE

Wilson's disease (WD), also known as hepatoleticular degeneration (HLD), is a rare autosomal recessive genetic disorder of copper metabolism, which causes copper to accumulate in body tissues. In this study, rats fed with copper-laden diet are used to render the clinical manifestations of WD, and their copper toxicity-induced organ lesions are studied. To investigate metabolic behaviors of 'decoppering' process, penicillamine (PA) was used for treating copper-laden rats as this chelating agent could eliminate excess copper through the urine. To date, there has been limited metabolomics study on WD, while metabolic impacts of copper accumulation and PA administration have yet to be established.

MATERIALS AND METHODS

A combination of 1HNMR spectroscopy and multivariate statistical analysis was applied to examine the metabolic profiles of the urine and blood serum samples collected from the copper-laden rat model of WD with PA treatment.

RESULTS

Copper accumulation in the copper-laden rats is associated with increased lactate, creatinine, valine and leucine, as well as decreased levels of glucose and taurine in the blood serum. There were also significant changes in p-hydroxyphenylacetate (p-HPA), creatinine, alpha-ketoglutarate (α-KG), dimethylamine, N-acetylglutamate (NAG), N-acetylglycoprotein (NAC) in the urine of these rats. Notably, the changes in p-HPA, glucose, lactate, taurine, valine, leucine, and NAG were found reversed following PA treatment. Nevertheless, there were no changes for dimethylamine, α-KG, and NAC as a result of the treatment. Compared with the controls, the concentrations of hippurate, formate, alanine, and lactate were changed when PA was applied and this is probably due to its side effect. A tool named SMPDB (Small Molecule Pathway Database) is introduced to identify the metabolic pathway influenced by the copper-laden diet.

CONCLUSION

The study has shown the potential application of NMR-based metabolomic analysis in providing further insights into the molecular mechanism underlying disorder due to WD.

Acclimatisation-induced stress influenced host metabolic and gut microbial composition change

An integrated metabonomics and metagenomics approach utilised here showed that acclimatisation-induced stress leads to host metabolic and gut microbiotal changes.

Metabolomic changes in patients with chronic obstructive pulmonary disease with abnormal Savda syndrome

The aim of this study was to determine the metabolic biomarkers for abnormal Savda syndrome in patients with chronic obstructive pulmonary disease (COPD). Based on Traditional Uyghur Medicine (TUM) theory, a total of 103 patients with COPD were classified into abnormal Savda and non-abnormal Savda syndrome groups and 52 healthy volunteers acted as the control group. Blood samples from the three groups were analyzed using nuclear magnetic resonance (NMR) spectroscopy combined with orthogonal projection to latent structure-discriminant analysis. NMR tests showed that the regional distributions of the patients with COPD with abnormal Savda syndrome, those with non-abnormal Savda syndrome and the control group were completely separate (P>0.05). The patients with COPD with abnormal Savda syndrome exhibited relatively low levels of amino acids, glycoproteins and unsaturated lipids (P<0.05) but significantly higher levels of lactic acid, carnitine, acetone and acetoacetate (P<0.05) compared with the healthy controls. Abnormal Savda syndrome was one of the main types of syndrome among the patients with COPD; increased age, a longer duration of illness and a higher disease severity were characteristic of this type of syndrome. In addition, the present study provided biochemical evidence for the TUM theory-based classification of patients with COPD; these biomarkers can be used in the clinic for the diagnosis of COPD with abnormal Savda syndrome. The study also demonstrated that the plasma metabolic disorder in patients with COPD with abnormal Savda syndrome was more serious than that in the control and COPD with non-abnormal Savda syndrome groups. The plasma metabolic disorder was also associated with a low immune function of the body and endocrine and energy metabolism disorders.

Metabolomics study on model rats of chronic obstructive pulmonary disease treated with Bu‑Fei Jian‑Pi

The therapeutic effect of Traditional Chinese Medicine (TCM) on chronic obstructive pulmonary disease (COPD) has been know for numerous years; however, the mechanism of action of the beneficial effects of TCM remains to be elucidated. The present study aimed to investigate the molecular mechanisms of COPD through metabolomic analysis as well as explore the targets and intervention mechanisms of TCM therapy using the common TCM granules Bu‑Fei Jian‑Pi. COPD rat models were established using smoke inhalations and recurrent bacterial infections. Rats were then divided into three groups as follows: A1, control healthy rats; B1, COPD model; and D1, Bu‑Fei Jian‑Pi‑treated COPD rats. Following administration of the medicine, the metabolomic profile of the lung tissue of rats in each group was assessed using high‑performance liquid chromatography/quadrupole‑time‑of‑flight mass spectrometry. The results demonstrated that there was a significanlty different spectrum of metabolites in the lung tissue of the model group compared to that of the control group as well as the Bu‑Fei Jian‑Pi‑treated COPD group; in addition, following treatment with Bu‑Fei Jian‑Pi, the metabolites of COPD rats were comparable with those of the control. Notable changes were observed in 31 metabolites between the Bu‑Fei Jian‑Pi‑treated group and the model group; however, there were 13 comparable metabolites between the Bu‑Fei Jian‑Pi and control groups as well as the model and control groups. Eleven metabolites showed a negative fold change in the Bu‑Fei Jian‑Pi‑treated groups compared to concentrations in the model group; however, minimal changes were observed in phenylpyruvic acid and α‑D‑fucose expression. In conclusion, the results of the present study demonstrated that Bu‑Fei Jian‑Pi granules had beneficial effects on measured outcomes in a rat model of stable COPD, indicated by a significantly different spectrum of metabolites. This therefore indicated that the metabolites which had significantly altered expression in the model group compared with that of the control and Bu‑Fei Jian‑Pi‑treated groups may be potential biomarkers of COPD.

Basics of mass spectrometry based metabolomics

The emerging field of metabolomics, aiming to characterize small molecule metabolites present in biological systems, promises immense potential for different areas such as medicine, environmental sciences, agronomy, etc. The purpose of this article is to guide the reader through the history of the field, then through the main steps of the metabolomics workflow, from study design to structure elucidation, and help the reader to understand the key phases of a metabolomics investigation and the rationale underlying the protocols and techniques used. This article is not intended to give standard operating procedures as several papers related to this topic were already provided, but is designed as a tutorial aiming to help beginners understand the concept and challenges of MS-based metabolomics. A real case example is taken from the literature to illustrate the application of the metabolomics approach in the field of doping analysis. Challenges and limitations of the approach are then discussed along with future directions in research to cope with these limitations. This tutorial is part of the International Proteomics Tutorial Programme (IPTP18).

Metabolomic fingerprinting: challenges and opportunities

Systems biology has primarily focused on studying genomics, transcriptomics, and proteomics and their dynamic interactions. These, however, represent only the potential for a biological outcome since the ultimate phenotype at the level of the eventually produced metabolites is not taken into consideration. The emerging field of metabolomics provides complementary guidance toward an integrated approach to this problem: It allows global profiling of the metabolites of a cell, tissue, or host and presents information on the actual end points of a response. A wide range of data collection methods are currently used and allow the extraction of global or tissue-specific metabolic profiles. The great amount and complexity of data that are collected require multivariate analysis techniques, but the increasing amount of work in this field has made easy-to-use analysis programs readily available. Metabolomics has already shown great potential in drug toxicity studies, disease modeling, and diagnostics and may be integrated with genomic and proteomic data in the future to provide in-depth understanding of systems, pathways, and their functionally dynamic interactions. In this review we discuss the current state of the art of metabolomics, its applications, and future potential.

Investigation into variation of endogenous metabolites in bone marrow cells and plasma in C3H/He mice exposed to benzene

Benzene is identified as a carcinogen. Continued exposure of benzene may eventually lead to damage to the bone marrow, accompanied by pancytopenia, aplastic anemia or leukemia. This paper explores the variations of endogenous metabolites to provide possible clues for the molecular mechanism of benzene-induced hematotoxicity. Liquid chromatography coupled with time of flight-mass spectrometry (LC-TOF-MS) and principal component analysis (PCA) was applied to investigate the variation of endogenous metabolites in bone marrow cells and plasma of male C3H/He mice. The mice were injected subcutaneously with benzene (0, 300, 600 mg/day) once daily for seven days. The body weights, relative organ weights, blood parameters and bone marrow smears were also analyzed. The results indicated that benzene caused disturbances in the metabolism of oxidation of fatty acids and essential amino acids (lysine, phenylalanine and tyrosine) in bone marrow cells. Moreover, fatty acid oxidation was also disturbed in plasma and thus might be a common disturbed metabolic pathway induced by benzene in multiple organs. This study aims to investigate the underlying molecular mechanisms involved in benzene hematotoxicity, especially in bone marrow cells.

Nutritional modulation of the metabonome: applications of metabolic phenotyping in translational nutritional research

PURPOSE OF REVIEW

Metabolic profiling technologies provide a global overview of complex dietary processes. Metabonomic analytical approaches have now been translated into multiple areas of clinical nutritional research based on the widespread adoption of high-throughput mass spectrometry and proton nuclear magnetic resonance spectroscopy. This has generated novel insights into the molecular mechanisms that shape the microbiome-dietary-chronic disease axis.

RECENT FINDINGS

Metabolome-wide association studies have created a new paradigm in nutritional molecular epidemiology and they have highlighted the importance of gut microbial cometabolic processes in the development of cardiovascular disease and diabetes. Targeted analyses are helping to explain the mechanisms by which high-risk diets (such as red meat) modulate disease risk and they are generating novel biomarkers that will serve to re-define how the efficacy of nutritional interventions is assessed. Nutritional metabonome-microbiome interactions have also been defined in extreme dietary states such as obesity and starvation, and they also serve as important models for understanding how the gut microbiome modifies disease risk. Finally, nutritional systems medicine approaches are creating novel insights into the functional components of our diet, and the mechanisms by which they cause disease.

SUMMARY

Diet is an important modulator of the human metabolic phenotype and the analysis of the nutritional metabolome will drive future development of personalized nutritional interventions.

1H-NMR-based metabolic analysis of human serum reveals novel markers of myocardial energy expenditure in heart failure patients

OBJECTIVE

Elevated myocardial energy expenditure (MEE) is related with reduced left ventricular ejection fraction, and has also been documented as an independent predictor of cardiovascular mortality. However, the serum small-molecule metabolite profiles and pathophysiological mechanisms of elevated MEE in heart failure (HF) are still lacking. Herein, we used 1H-NMR-based metabolomics analysis to screen for potential biomarkers of MEE in HF.

METHODS

A total of 61 subjects were enrolled, including 46 patients with heart failure and 15 age-matched controls. Venous serum samples were collected from subjects after an 8-hour fast. An INOVA 600 MHz nuclear magnetic resonance spectrometer with Carr-Purcell-Melboom-Gill (CPMG) pulse sequence was employed for the metabolomics analysis and MEE was calculated using colored Doppler echocardiography. Metabolomics data were processed using orthogonal signal correction and regression analysis was performed using the partial least squares method.

RESULTS

The mean MEE levels of HF patients and controls were 139.61±58.18 cal/min and 61.09±23.54 cal/min, respectively. Serum metabolomics varied with MEE changed, and 3-hydroxybutyrate, acetone and succinate were significantly elevated with the increasing MEE. Importantly, these three metabolites were independent of administration of angiotensin converting enzyme inhibitor, β-receptor blockers, diuretics and statins (P>0.05).

CONCLUSIONS

These results suggested that in patients with heart failure, MEE elevation was associated with significant changes in serum metabolomics profiles, especially the concentration of 3-hydroxybutyrate, acetone and succinate. These compounds could be used as potential serum biomarkers to study myocardial energy mechanism in HF patients.

Pattern recognition analysis for hepatotoxicity induced by acetaminophen using plasma and urinary 1H NMR-based metabolomics in humans

Drug-induced liver injury (DILI) is currently an increasingly relevant health issue. However, available biomarkers do not reliably detect or quantify DILI risk. Therefore, the purpose of this study was to comparatively evaluate plasma and urinary biomarkers obtained from humans treated with acetaminophen (APAP) using a metabolomics approach and a proton nuclear magnetic resonance (NMR) platform. APAP (3 g/day, two 500 mg tablets every 8 h) was administered to 20 healthy Korean males (age, 20-29 years) for 7 days. Urine was collected daily before and during dosing and 6 days after the final dose. NMR spectra of these urine samples were analyzed using principal component analysis (PCA) and partial least-squares-discrimination analysis. Although the activities of aspartate aminotransferase and lactate dehydrogenase were significantly increased 7 days post-APAP treatment, serum biochemical parameters of aspartate aminotransferase, alanine aminotransferase, alkaline phosphatase, total bilirubin, γ-glutamyl transpeptidase, and lactate dehydrogenase were within normal range of hepatic function. However, urine and plasma (1)H NMR spectroscopy revealed different clustering between predosing and after APAP treatment for global metabolomic profiling through PCA. Urinary endogenous metabolites of trimethylamine-N-oxide, citrate, 3-chlorotyrosine, phenylalanine, glycine, hippurate, and glutarate as well as plasma endogenous metabolites such as lactate, glucose, 3-hydroxyisovalerate, isoleucine, acetylglycine, acetone, acetate, glutamine, ethanol, and isobutyrate responded significantly to APAP dosing in humans. Urinary and plasma endogenous metabolites were more sensitive than serum biochemical parameters. These results might be applied to predict or screen potential hepatotoxicity caused by other drugs using urinary and plasma (1)H NMR analyses.

Metabonomics study of the therapeutic mechanism of Gynostemma pentaphyllum and atorvastatin for hyperlipidemia in rats

Gynostemma pentaphyllum (GP) is widely used for the treatment of diseases such as hyperlipidemia, fatty liver and obesity in China, and atorvastatin is broadly used as an anti-hyperlipidemia drug. This research focuses on the plasma and liver metabolites in the following four groups of rats: control, a hyperlipidemia model, a hyperlipidemia model treated with GP and a hyperlipidemia model treated with atorvastatin. Using ¹H-NMR-based metabonomics, we elucidated the therapeutic mechanisms of GP and atorvastatin. Orthogonal Partial Least Squares-Discriminant analysis (OPLS-DA) plotting of the metabolic state and analysis of potential biomarkers in the plasma and liver correlated well with the results of biochemical assays. GP can effectively affect lipid metabolism, and it exerts its anti-hyperlipidemia effect by elevating the level of phosphatidylcholine and decreasing the level of trimethylamine N-oxide (TMAO). In contrast, atorvastatin affects hyperlipidemia mainly during lipid metabolism and protein metabolism in vivo.

The impact of inflammation on metabolomic profiles in patients with arthritis

Objective. Inflammatory arthritis is associated with systemic manifestations including alterations in metabolism. We used nuclear magnetic resonance (NMR) spectroscopy–based metabolomics to assess metabolic fingerprints in serum from patients with established rheumatoid arthritis (RA) and those with early arthritis.

Methods. Serum samples were collected from newly presenting patients with established RA who were naive for disease-modifying antirheumatic drugs, matched healthy controls, and 2 groups of patients with synovitis of ≤3 months' duration whose outcomes were determined at clinical followup. Serum metabolomic profiles were assessed using 1-dimensional ¹H-NMR spectroscopy. Discriminating metabolites were identified, and the relationships between metabolomic profiles and clinical variables including outcomes were examined.

Results. The serum metabolic fingerprint in established RA was clearly distinct from that of healthy controls. In early arthritis, we were able to stratify the patients according to the level of current inflammation, with C-reactive protein correlating with metabolic differences in 2 separate groups (P < 0.001). Lactate and lipids were important discriminators of inflammatory burden in both early arthritis patient groups. The sensitivities and specificities of models to predict the development of either RA or persistent arthritis in patients with early arthritis were low.

Conclusion. The metabolic fingerprint reflects inflammatory disease activity in patients with synovitis, demonstrating that underlying inflammatory processes drive significant changes in metabolism that can be measured in the peripheral blood. The identification of metabolic alterations may provide insights into disease mechanisms operating in patients with inflammatory arthritis.

Effects of low doses of bisphenol A on the metabolome of perinatally exposed CD-1 mice

BACKGROUND

Bisphenol A (BPA) is a well-known endocrine disruptor used to manufacture polycarbonate plastics and epoxy resins. Exposure of pregnant rodents to low doses of BPA results in pleiotropic effects in their offspring.

OBJECTIVE

We used metabolomics--a method for determining metabolic changes in response to nutritional, pharmacological, or toxic stimuli--to examine metabolic shifts induced in vivo by perinatal exposure to low doses of BPA in CD-1 mice.

METHODS

Male offspring born to pregnant CD-1 mice that were exposed to vehicle or to 0.025, 0.25, or 25 µg BPA/kg body weight/day, from gestation day 8 through day 16 of lactation, were examined on postnatal day (PND) 2 or PND21. Aqueous extracts of newborns (PND2, whole animal) and of livers, brains, and serum samples from PND21 pups were submitted to (1)H nuclear magnetic resonance spectroscopy. Data were analyzed using partial least squares discriminant analysis.

RESULTS

Examination of endogenous metabolic fingerprints revealed remarkable discrimination in whole extracts of the four PND2 newborn treatment groups, strongly suggesting changes in the global metabolism. Furthermore, statistical analyses of liver, serum, and brain samples collected on PND21 successfully discriminated among treatment groups. Variations in glucose, pyruvate, some amino acids, and neurotransmitters (γ-aminobutyric acid and glutamate) were identified.

CONCLUSIONS

Low doses of BPA disrupt global metabolism, including energy metabolism and brain function, in perinatally exposed CD-1 mouse pups. Metabolomics can be used to highlight the effects of low doses of endocrine disruptors by linking perinatal exposure to changes in global metabolism.

A Systematic, Integrated Study on the Neuroprotective Effects of Hydroxysafflor Yellow A Revealed by (1)H NMR-Based Metabonomics and the NF-κB Pathway

Hydroxysafflor yellow A (HSYA) is the main active component of the Chinese herb Carthamus tinctorius L.. Purified HSYA is used as a neuroprotective agent to prevent cerebral ischemia. Injectable safflor yellow (50 mg, containing 35 mg HSYA) is widely used to treat patients with ischemic cardiocerebrovascular disease. However, it is unknown how HSYA exerts a protective effect on cerebral ischemia at the molecular level. A systematical integrated study, including histopathological examination, neurological evaluation, blood-brain barrier (BBB), metabonomics, and the nuclear factor-κB (NF-κB) pathway, was applied to elucidate the pathophysiological mechanisms of HSYA neuroprotection at the molecular level. HSYA could travel across the BBB, significantly reducing the infarct volume and improving the neurological functions of rats with ischemia. Treatment with HSYA could lead to relative corrections of the impaired metabolic pathways through energy metabolism disruption, excitatory amino acid toxicity, oxidative stress, and membrane disruption revealed by (1)H NMR-based metabonomics. Meanwhile, HSYA treatment inhibits the NF-κB pathway via suppressing proinflammatory cytokine expression and p65 translocation and binding activity while upregulating an anti-inflammatory cytokine.

1H-NMR based metabonomic profiling of human esophageal cancer tissue

BACKGROUND

The biomarker identification of human esophageal cancer is critical for its early diagnosis and therapeutic approaches that will significantly improve patient survival. Specially, those that involves in progression of disease would be helpful to mechanism research.

METHODS

In the present study, we investigated the distinguishing metabolites in human esophageal cancer tissues (n = 89) and normal esophageal mucosae (n = 26) using a (1)H nuclear magnetic resonance ((1)H-NMR) based assay, which is a highly sensitive and non-destructive method for biomarker identification in biological systems. Principal component analysis (PCA), partial least squares-discriminant analysis (PLS-DA) and orthogonal partial least-squares-discriminant analysis (OPLS-DA) were applied to analyse (1)H-NMR profiling data to identify potential biomarkers.

RESULTS

The constructed OPLS-DA model achieved an excellent separation of the esophageal cancer tissues and normal mucosae. Excellent separation was obtained between the different stages of esophageal cancer tissues (stage II = 28; stage III = 45 and stage IV = 16) and normal mucosae. A total of 45 metabolites were identified, and 12 of them were closely correlated with the stage of esophageal cancer. The downregulation of glucose, AMP and NAD, upregulation of formate indicated the large energy requirement due to accelerated cell proliferation in esophageal cancer. The increases in acetate, short-chain fatty acid and GABA in esophageal cancer tissue revealed the activation of fatty acids metabolism, which could satisfy the need for cellular membrane formation. Other modified metabolites were involved in choline metabolic pathway, including creatinine, creatine, DMG, DMA and TMA. These 12 metabolites, which are involved in energy, fatty acids and choline metabolism, may be associated with the progression of human esophageal cancer.

CONCLUSION

Our findings firstly identify the distinguishing metabolites in different stages of esophageal cancer tissues, indicating the attribution of metabolites disturbance to the progression of esophageal cancer. The potential biomarkers provide a promising molecular diagnostic approach for clinical diagnosis of human esophageal cancer and a new direction for the mechanism study.

Perspectives for metabolomics in testosterone replacement therapy

Testosterone is the major circulating androgen in men but exhibits an age-related decline in the ageing male. Late-onset hypogonadism or androgen deficiency syndrome (ADS) is a 'syndromic' disorder including both a persistent low testosterone serum concentration and major clinical symptoms, including erectile dysfunction, low libido, decreased muscle mass and strength, increased body fat, decreased vitality or depressed mood. Given its unspecific symptoms, treatment goals and monitoring parameters, this review will outline the various uncertainties concerning the diagnosis, therapy and monitoring of ADS to date. Literature was identified primarily through searches for specific investigators in the PubMed database. No date or language limits were applied in the literature search for the present review. The current state of research, showing that metabolomics is starting to have an impact not only on disease diagnosis and prognosis but also on drug treatment efficacy and safety monitoring, will be presented, and the application of metabolomics to improve the clinical management of ADS will be discussed. Finally, the scientific opportunities presented by metabolomics and other -omics as novel and promising tools for biomarker discovery and individualised testosterone replacement therapy in men will be explored.

Discrimination of type 2 diabetes mellitus corresponding to different traditional Chinese medicine syndromes based on plasma fatty acid profiles and chemometric methods

AIMS OF THE STUDY

Traditional Chinese medicine (TCM) has a long history and particular advantages in the diagnosis and treatment of type 2 diabetes mellitus (T2DM). Syndrome differentiation is the foundation and essence of TCM theories. The aims of the study are to discriminate T2DM corresponding to different syndromes (Qi-deficiency, Qi and Yin-deficiency and Damp heat) and discover syndrome-related biomarkers using metabolomics technology.

MATERIALS AND METHODS

Plasma fatty acid profiles of 85 clinical samples were established by high performance liquid chromatography (HPLC). Moreover, some of the lipid parameters, including total cholesterol (TC), triglycerides (TG), high-density lipoprotein (HDL) and low-density lipoprotein (LDL), were obtained through clinical testing methods. Orthogonal signal correction-partial least squares (OSC-PLS) and uncorrelated linear discriminant analysis (ULDA) were employed to establish two-class models for three different syndromes.

RESULTS

Compared with the plasma fatty acid profiles of healthy controls, the characteristic fatty acids of three TCM syndromes were discovered (p<0.01). Totally, the plasma fatty acids of T2DM were up-regulated, while significant differences existed in different syndromes. Results of ULDA indicate that the three TCM syndromes could be effectively separated by the plasma fatty acid profiles and the syndrome-related biomarkers were also screened.

CONCLUSIONS

The fact that three TCM syndromes can be separated indicates certain metabolic differences in different TCM syndromes of T2DM really exist and such differences can be manifested by fatty acids and lipid parameters. The results benefit modern biological interpretation of the three TCM syndromes and in a sense the diagnosis and treatment of diabetes.

1H Nuclear Magnetic Resonance (NMR) Metabolomic Study of Chronic Organophosphate Exposure in Rats

1H NMR spectroscopy and chemometric analysis were used to characterize rat urine obtained after chronic exposure to either tributyl phosphate (TBP) or triphenyl phosphate (TPP). In this study, the daily dose exposure was 1.5 mg/kg body weight for TBP, or 2.0 mg/kg body weight for TPP, administered over a 15-week period. Orthogonal signal correction (OSC) -filtered partial least square discriminant analysis (OSC-PLSDA) was used to predict and classify exposure to these organophosphates. During the development of the model, the classification error was evaluated as a function of the number of latent variables. NMR spectral regions and corresponding metabolites important for determination of exposure type were identified using variable importance in projection (VIP) coefficients obtained from the OSC-PLSDA analysis. As expected, the model for classification of chronic (1.5-2.0 mg/kg body weight daily) TBP or TPP exposure was not as strong as the previously reported model developed for identifying acute (15-20 mg/kg body weight) exposure. The set of majorly impacted metabolites identified for chronic TBP or TPP exposure was slightly different than those metabolites previously identified for acute exposure. These metabolites were then mapped to different metabolite pathways and ranked, allowing the metabolic response to chronic organophosphate exposure to be addressed.

Revealing metabolite biomarkers for acupuncture treatment by linear programming based feature selection

Background

Acupuncture has been practiced in China for thousands of years as part of the Traditional Chinese Medicine (TCM) and has gradually accepted in western countries as an alternative or complementary treatment. However, the underlying mechanism of acupuncture, especially whether there exists any difference between varies acupoints, remains largely unknown, which hinders its widespread use.

Results

In this study, we develop a novel Linear Programming based Feature Selection method (LPFS) to understand the mechanism of acupuncture effect, at molecular level, by revealing the metabolite biomarkers for acupuncture treatment. Specifically, we generate and investigate the high-throughput metabolic profiles of acupuncture treatment at several acupoints in human. To select the subsets of metabolites that best characterize the acupuncture effect for each meridian point, an optimization model is proposed to identify biomarkers from high-dimensional metabolic data from case and control samples. Importantly, we use nearest centroid as the prototype to simultaneously minimize the number of selected features and the leave-one-out cross validation error of classifier. We compared the performance of LPFS to several state-of-the-art methods, such as SVM recursive feature elimination (SVM-RFE) and sparse multinomial logistic regression approach (SMLR). We find that our LPFS method tends to reveal a small set of metabolites with small standard deviation and large shifts, which exactly serves our requirement for good biomarker. Biologically, several metabolite biomarkers for acupuncture treatment are revealed and serve as the candidates for further mechanism investigation. Also biomakers derived from five meridian points, Zusanli (ST36), Liangmen (ST21), Juliao (ST3), Yanglingquan (GB34), and Weizhong (BL40), are compared for their similarity and difference, which provide evidence for the specificity of acupoints.

Conclusions

Our result demonstrates that metabolic profiling might be a promising method to investigate the molecular mechanism of acupuncture. Comparing with other existing methods, LPFS shows better performance to select a small set of key molecules. In addition, LPFS is a general methodology and can be applied to other high-dimensional data analysis, for example cancer genomics.

¹H NMR-based metabonomics in brain nucleus accumbens and striatum following repeated cocaine treatment in rats

Studies have shown a few cerebral metabolites modified by cocaine in brain regions; however, endogenous metabolic profiling has been lacking. Ex vivo (1)H NMR (hydrogen-1 nuclear magnetic resonance) spectroscopy-based metabonomic approach coupled with partial least squares was applied to investigate the changes of cerebral metabolites in nucleus accumbens (NAc) and striatum of rats subjected to cocaine treatment. Our results showed that both single and repeated cocaine treatment can induce significant changes in a couple of cerebral metabolites. The increase of neurotransmitters glutamate and gamma-amino butyric acid (GABA) were observed in NAc and striatum from the rats repeatedly treated with cocaine. Creatine and taurine increased in NAc whereas taurine increased and creatine decreased in striatum after repeated cocaine treatment. Elevation of N-acetylaspartate in NAc and striatum and decrease of lactate in striatum were observed, which may reflect the mitochondria dysregulation caused by cocaine; moreover, alterations of choline, phosphocholine and glycerol in NAc and striatum could be related to membrane disruption. Moreover, groups of rats with and without conditioned place preference (CPP) apparatus are presenting difference in metabolites. Collectively, our results provide the first evidence of metabonomic profiling of NAc and striatum in response to cocaine, exhibiting a regionally-specific alteration patterns. We find that repeated cocaine administration leads to significant metabolite alterations, which are involved in neurotransmitter disturbance, oxidative stress, mitochondria dysregulation and membrane disruption in brain.

Metabolomic analysis of the plasma of patients with high-altitude pulmonary edema (HAPE) using 1H NMR

Upon rapid ascent to a high altitude, non-acclimatized individuals, although healthy, are highly prone to contracting high-altitude pulmonary edema (HAPE). Early diagnosis is difficult and there is no reliable biomarker available. We used proton ((1)H) NMR metabolomics to profile the altered metabolic patterns of blood plasma from HAPE patients. The plasmas of ten patients with HAPE and ten individuals without HAPE were collected and compared using (1)H NMR spectroscopy. Data were evaluated with several multivariate statistical analyses, including the principal components, the orthogonal partial least-squares discriminant, and the orthogonal signal correction partial least-squares discriminant. Multivariate statistical analyses revealed a significant disparity between subjects with HAPE and those in the control group. Compared to the plasma of the controls, the HAPE patients had significant increases in valine, lysine, leucine, isoleucine, glycerol phosphoryl choline, glycine, glutamine, glutamic acid, creatinine, citrate, and methyl histidine. These were accompanied by decreases in α- and β-glucose, trimethylamine, and the metabolic products of lipids. The data demonstrate that metabolomics may be effective for the diagnosis of HAPE in the future, and can be used for further understanding HAPE pathogenesis.

Beneficial metabolic effects of 2',3',5'-tri-acetyl-N6- (3-hydroxylaniline) adenosine in the liver and plasma of hyperlipidemic hamsters

Background

Pharmaceutical research of hyperlipidemia has been commonly pursued using traditional approaches. However, unbiased metabonomics attempts to explore the metabolic signature of hyperlipidemia in a high-throughput manner to understand pathophysiology of the disease process.

Methodology/Principal Findings

As a new way, we performed ¹H NMR-based metabonomics to evaluate the beneficial effects of 2′,3′,5′-tri-acetyl-N₆- (3-hydroxylaniline) adenosine (WS070117) on plasma and liver from hyperlipidemic Syrian golden hamsters. Both plasma and liver profiles provided a clearer distinction between the control and hyperlipidemic hamsters. Compared to control animals, hyperlipidemic hamsters showed a higher content of lipids (triglyceride and cholesterol), lactate and alanine together with a lower content of choline-containing compounds (e.g., phosphocholine, phosphatidylcholine, and glycerophosphocholine) and betaine. As a result, metabonomics-based findings such as the PCA and OPLS-DA plotting of metabolic state and analysis of potential biomarkers in plasma and liver correlated well to the assessment of biochemical assays, Oil Red O staining and in vivo ultrasonographic imaging suggesting that WS070117 was able to regulate lipid content and displayed more beneficial effects on plasma and liver than simvastatin.

Conclusions/Significance

This work demonstrates the promise of applying ¹H NMR metabonomics to evaluate the beneficial effects of WS070117 which may be a good drug candidate for hyperlipidemia.

¹H NMR-based metabonomic analysis of brain in rats of morphine dependence and withdrawal intervention

Metabolic consequences of morphine dependence and withdrawal intervention have not been well explored. In the present study, the metabolic changes in brain hippocampus, nucleus accumbens (NAc), prefrontal cortex (PFC) and striatum of rats with morphine dependence and withdrawal intervention were explored by using ¹H nuclear magnetic resonance coupled with principal component analysis, partial least squares and orthogonal signal correction analysis. We found that the concentrations of neurotransmitters including glutamate, glutamine and gamma-aminobutyric acid changed differentially in hippocampus, NAc, PFC and striatum after repeated morphine treatment. Significant changes were also found in a number of cerebral metabolites including N-acetyl aspartate (NAA), lactic acid, creatine, myo-inositol and taurine. These findings indicate the profound disturbances of energy metabolism, amino acid metabolism and neurotransmitters caused by chronic morphine treatment. Interestingly, morphine-induced changes in lactic acid, creatine and NAA were clearly reversed by intervention of methadone or clonidine. Our study provides a comprehensive understanding of the metabolic alteration associated with morphine addiction and withdrawal therapy, which may help to develop new pharmacotherapies.